Chinese Handwriting Recognition: An Algorithmic Perspective

This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focuse...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Su, Tonghua (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:SpringerBriefs in Electrical and Computer Engineering,
Temas:
Image processing-Digital techniques.
Computer vision.
Pattern recognition systems.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Automated Pattern Recognition.
Computer Vision.
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Chinese Handwriting Recognition: An Algorithmic Perspective  |h [electronic resource] /  |c by Tonghua Su. 
250 |a 1st ed. 2013. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013. 
300 |a XI, 124 p. 62 illus., 16 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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505 0 |a Introduction -- HIT-MW Database -- Integrated Segmentation-Recognition Strategy -- Segmentation-free Strategy: Basic Algorithms -- Segmentation-free Strategy: Advanced Algorithms. 
520 |a This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focused on. Baseline systems are initially presented for these strategies and are subsequently expanded on and incrementally improved. The sophisticated algorithms covered include: 1) string sample expansion algorithms which synthesize string samples from isolated characters or distort realistic string samples; 2) enhanced feature representation algorithms, e.g. enhanced four-plane features and Delta features; 3) novel learning algorithms, such as Perceptron learning with dynamic margin, MPE training and distributed training; and lastly 4) ensemble algorithms, that is, combining the two strategies using both parallel structure and serial structure. All the while, the book moves from basic to advanced algorithms, helping readers quickly embark on the study of Chinese handwriting recognition. 
650 0 |a Image processing-Digital techniques. 
650 0 |a Computer vision. 
650 0 |a Pattern recognition systems. 
650 1 4 |a Computer Imaging, Vision, Pattern Recognition and Graphics. 
650 2 4 |a Automated Pattern Recognition. 
650 2 4 |a Computer Vision. 
710 2 |a SpringerLink (Online service) 
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